National Instruments Corporation

Stephen Thung

Shaul Teplinsky

James C Nagle

Douglas William Farrell

Sergey Kizunov

Jeffrey Marcus Monroe

Walter Michael Altmann

Peter Andrew Kurlak

Techniques for assigning scenario-based tests to test assets are described. In an example, a scenario-based test operable to test a key performance indicator (KPI) of a System Under Test (SUT), a component behavior exhibited by a first component of the SUT, and a scenario characteristic are received. Based on the component behavior and the scenario characteristic, a first plurality of behavior models associated with the component behavior are identified. Based on the scenario characteristic a characteristic value is extracted from the scenario-based test. Each behavior model of the first plurality of behavior models is executed using the characteristic value to generate a first plurality of predicted behavior outcomes. Based on the first plurality of predicted behavior outcomes, a first test asset type from a plurality of test asset types is selected and the scenario-based test is transmitted to a test asset of the first test asset type.

System and method of adaptively assigning scenario-based tests to test assets

Methods, computing devices, and software programs for identifying a driving scenario in real-time driving data. A driving scenario is received and translated into an ordered sequence of events that correspond to the driving scenario. A signal computation function is determined for each event in the sequence, which quantifies proximity to the respective event. Driving data is received for a plurality of time steps. Values of each signal computation function are determined, evaluated for the driving data at each of the plurality of time steps. It is determined whether the driving scenario has occurred in the driving data based on the values of the signal computation function. A first portion of the driving data is either modified, discarded, or stored in memory based on the determination whether the driving scenario has occurred.

Edge data reduction in automotive systems

Described herein are systems, methods, and other techniques for identifying redundant parameters and reducing parameters for testing a device. A set of test values and limits for a set of parameters are received. A set of simulated test values for the set of parameters are determined based on one or more probabilistic representations for the set of parameters. The one or more probabilistic representations are constructed based on the set of test values. A set of cumulative probabilities of passing for the set of parameters are calculated based on the set of simulated test values and the limits. A reduced set of parameters are determined from the set of parameters based on the set of cumulative probabilities of passing. The reduced set of parameters are deployed for testing the device.

Parameter space reduction for device testing

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Stephen Thung